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Training memory-constrained deep learning models using automatic dataflow-graph partitioning

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dc.contributor.advisorErten, Didem Unat
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorQararyah, Fareed Mohammad
dc.contributor.programComputer Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.coverage.spatialİstanbul
dc.date.accessioned2024-11-09T22:06:46Z
dc.date.issued2020
dc.format.extentxv, 59 leaves : tables, graphics ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4877
dc.language.isoeng
dc.publisherKoç University
dc.relation.collectionKU Theses and Dissertations
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectNeural networks (Computer science)
dc.subjectDeep learning
dc.subjectComputational learning theory
dc.subjectMachine learning
dc.subjectArtificial intelligence
dc.titleTraining memory-constrained deep learning models using automatic dataflow-graph partitioning
dc.typeThesis
dspace.entity.typePublication
local.contributor.kuauthorQararyah, Fareed Mohammad
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